diff --git a/docs/docs/examples/chat-memory.mdx b/docs/docs/examples/chat-memory.mdx
index 88dbbca2b..174711ce8 100644
--- a/docs/docs/examples/chat-memory.mdx
+++ b/docs/docs/examples/chat-memory.mdx
@@ -8,7 +8,7 @@ import Admonition from "@theme/Admonition";
 
 The **Chat Memory** component restores previous messages given a Session ID, which can be any string.
 
-This component is available under the **Helpers** tab of the Langflow preview.
+This component is available under the **Helpers** tab of the Langflow sidebar.
 
 <div
   style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
diff --git a/docs/docs/examples/combine-text.mdx b/docs/docs/examples/combine-text.mdx
index 5a4e86cf0..6fb46555f 100644
--- a/docs/docs/examples/combine-text.mdx
+++ b/docs/docs/examples/combine-text.mdx
@@ -12,7 +12,7 @@ The **Combine Text** component concatenates two text inputs into a single chunk
 
 Also, check out **Combine Texts (Unsorted)** as a similar alternative.
 
-This component is available under the **Helpers** tab of the Langflow preview.
+This component is available under the **Helpers** tab of the Langflow sidebar.
 
 <div
   style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
diff --git a/docs/docs/getting-started/rag-with-astradb.mdx b/docs/docs/getting-started/rag-with-astradb.mdx
index eff9973dc..c719d8d94 100644
--- a/docs/docs/getting-started/rag-with-astradb.mdx
+++ b/docs/docs/getting-started/rag-with-astradb.mdx
@@ -19,9 +19,8 @@ In this guide, we will use Astra DB as a vector store to store and retrieve the
 TLDR;
 
 - [Create a free Astra DB account](https://astra.datastax.com/signup?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=create-a-free-astra-db-account)
-- Duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
 - Create a new database, get a **Token** and the **API Endpoint**
-- Click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components
+- Start Langflow and click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components
 - Import the project into Langflow by dropping it on the Workspace or My Collection page
 - Update the **Token** and **API Endpoint** in the **Astra DB** components
 - Update the OpenAI API key in the **OpenAI** components
@@ -71,16 +70,12 @@ Once your database is initialized, to the right of the page, you will see the _D
 
 Now we are all set to start building our RAG application using Astra DB and Langflow.
 
-## (Optional) Duplicate the Langflow 1.0 HuggingFace Space
-
-If you haven't already, now is the time to launch Langflow. To make things easier, you can duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) which sets up a Langflow instance just for you.
-
 ## Open the Vector Store RAG Project
 
 To get started, click on the **New Project** button and look for the **Vector Store RAG** project. This will open a starter project with the necessary components to run a RAG application using Astra DB.
 
 <ZoomableImage
-  alt="Docusaurus themed image"
+  alt="Drag-and-drop"
   sources={{
     light: "img/drag-and-drop-flow.png",
     dark: "img/drag-and-drop-flow.png",
@@ -100,7 +95,7 @@ The ingestion flow consists of:
 - **Astra DB** component that stores the text chunks in the Astra DB database
 
 <ZoomableImage
-  alt="Docusaurus themed image"
+  alt="Astra Ingestion"
   sources={{
     light: "img/astra-ingestion-flow.png",
     dark: "img/astra-ingestion-flow.png",
@@ -122,7 +117,7 @@ Now, let's update the **Astra DB** and **Astra DB Search** components with the *
 And run it! This will ingest the Text data from your file into the Astra DB database.
 
 <ZoomableImage
-  alt="Docusaurus themed image"
+  alt="Astra Run"
   sources={{
     light: "img/astra-ingestion-run.png",
     dark: "img/astra-ingestion-run.png",
@@ -155,7 +150,7 @@ The RAG flow is a bit more complex. It consists of:
 To run it all we have to do is click on the ⚡ _Run_ button and start interacting with your RAG application.
 
 <ZoomableImage
-  alt="Docusaurus themed image"
+  alt="Astra RAG"
   sources={{
     light: "img/astra-rag-flow-run.png",
     dark: "img/astra-rag-flow-run.png",
@@ -168,7 +163,7 @@ This opens the Playground where you can chat your data.
 Because this flow has a **Chat Input** and a **Text Output** component, the Panel displays a chat input at the bottom and the Extracted Chunks section on the left.
 
 <ZoomableImage
-  alt="Docusaurus themed image"
+  alt="Playground"
   sources={{
     light: "img/astra-rag-flow-interaction-panel.png",
     dark: "img/astra-rag-flow-interaction-panel.png",
@@ -179,7 +174,7 @@ Because this flow has a **Chat Input** and a **Text Output** component, the Pane
 Once we interact with it we get a response and the Extracted Chunks section is updated with the retrieved data.
 
 <ZoomableImage
-  alt="Docusaurus themed image"
+  alt="Astra Playground"
   sources={{
     light: "img/astra-rag-flow-interaction-panel-interaction.png",
     dark: "img/astra-rag-flow-interaction-panel-interaction.png",
diff --git a/docs/docs/index.mdx b/docs/docs/index.mdx
index c6b6e0e71..7e85c97cd 100644
--- a/docs/docs/index.mdx
+++ b/docs/docs/index.mdx
@@ -29,11 +29,13 @@ Its intuitive interface allows for easy manipulation of AI building blocks, enab
 
 - [Langflow Workspace](/getting-started/workspace) - Learn more about the Langflow Workspace.
 
-<Admonition type="info">
-  Langflow is also available in HuggingFace Spaces. [Clone the space using this
-  link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
-  to run your own Langflow instance in minutes.
-</Admonition>
+{/* Mentions wrong link */}
+{/\* <Admonition type="info">
+Langflow is also available in HuggingFace Spaces. [Clone the space using this
+link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
+to run your own Langflow instance in minutes.
+
+</Admonition> */}
 
 ## Learn more about Langflow 1.0
 
diff --git a/docs/docs/starter-projects/basic-prompting.mdx b/docs/docs/starter-projects/basic-prompting.mdx
index 4e01f2472..594990eb6 100644
--- a/docs/docs/starter-projects/basic-prompting.mdx
+++ b/docs/docs/starter-projects/basic-prompting.mdx
@@ -18,13 +18,6 @@ This article demonstrates how to use Langflow's prompt tools to issue basic prom
 
 - [OpenAI API key created](https://platform.openai.com)
 
-<Admonition type="info">
-  Langflow is also available in HuggingFace Spaces. [Clone the space
-  using this
-  link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
-  to create your own Langflow workspace in minutes.
-</Admonition>
-
 ## Create the basic prompting project
 
 1. From the Langflow dashboard, click **New Project**.
@@ -62,4 +55,4 @@ This should be interesting...
    The **Edit Prompt** window opens.
 2. Change `Answer the user as if you were a pirate` to a different character, perhaps `Answer the user as if you were Harold Abelson.`
 3. Run the basic prompting flow again.
-   The response will be markedly different.
\ No newline at end of file
+   The response will be markedly different.
diff --git a/docs/docs/starter-projects/blog-writer.mdx b/docs/docs/starter-projects/blog-writer.mdx
index efaad8030..1c19c06b6 100644
--- a/docs/docs/starter-projects/blog-writer.mdx
+++ b/docs/docs/starter-projects/blog-writer.mdx
@@ -14,12 +14,13 @@ Build a blog writer with OpenAI that uses URLs for reference content.
 
 - [OpenAI API key created](https://platform.openai.com)
 
-<Admonition type="info">
-  Langflow is also available in HuggingFace Spaces. [Clone the space
-  using this
-  link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
-  to create your own Langflow workspace in minutes.
-</Admonition>
+{/\* <Admonition type="info">
+Langflow is also available in HuggingFace Spaces. [Clone the space
+using this
+link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
+to create your own Langflow workspace in minutes.
+
+</Admonition> */}
 
 ## Create the Blog Writer project
 
diff --git a/docs/docs/starter-projects/document-qa.mdx b/docs/docs/starter-projects/document-qa.mdx
index 952285cdb..2e452522e 100644
--- a/docs/docs/starter-projects/document-qa.mdx
+++ b/docs/docs/starter-projects/document-qa.mdx
@@ -14,13 +14,6 @@ Build a question-and-answer chatbot with a document loaded from local memory.
 
 - [OpenAI API key created](https://platform.openai.com)
 
-<Admonition type="info">
-  Langflow is also available in HuggingFace Spaces. [Clone the space
-  using this
-  link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
-  to create your own Langflow workspace in minutes.
-</Admonition>
-
 ## Create the Document QA project
 
 1. From the Langflow dashboard, click **New Project**.
diff --git a/docs/docs/starter-projects/memory-chatbot.mdx b/docs/docs/starter-projects/memory-chatbot.mdx
index 8997170f8..bf5a428ca 100644
--- a/docs/docs/starter-projects/memory-chatbot.mdx
+++ b/docs/docs/starter-projects/memory-chatbot.mdx
@@ -14,13 +14,6 @@ This flow extends the [basic prompting flow](./basic-prompting) to include chat
 
 - [OpenAI API key created](https://platform.openai.com)
 
-<Admonition type="info">
-  Langflow is also available in HuggingFace Spaces. [Clone the space
-  using this
-  link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
-  to create your own Langflow workspace in minutes.
-</Admonition>
-
 ## Create the memory chatbot project
 
 1. From the Langflow dashboard, click **New Project**.
@@ -81,4 +74,4 @@ To store **Session ID** as a Langflow variable, in the **Session ID** field, cli
 1. In the **Variable Name** field, enter a name like `customer_chat_emea`.
 2. In the **Value** field, enter a value like `1B5EBD79-6E9C-4533-B2C8-7E4FF29E983B`.
 3. Click **Save Variable**.
-4. Apply this variable to **Chat Input**.
\ No newline at end of file
+4. Apply this variable to **Chat Input**.
diff --git a/docs/docs/starter-projects/vector-store-rag.mdx b/docs/docs/starter-projects/vector-store-rag.mdx
index 120978439..4354295d8 100644
--- a/docs/docs/starter-projects/vector-store-rag.mdx
+++ b/docs/docs/starter-projects/vector-store-rag.mdx
@@ -16,13 +16,6 @@ We've chosen [Astra DB](https://astra.datastax.com/signup?utm_source=langflow-pr
 
 ## Prerequisites
 
-<Admonition type="info">
-  Langflow is also available in HuggingFace Spaces. [Clone the space
-  using this
-  link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
-  to create your own Langflow workspace in minutes.
-</Admonition>
-
 - [Langflow installed and running](../getting-started/install-langflow)
 
 - [OpenAI API key](https://platform.openai.com)
diff --git a/docs/docs/tutorials/rag-with-astradb.mdx b/docs/docs/tutorials/rag-with-astradb.mdx
index 6cf5c172d..e3f4a3f1e 100644
--- a/docs/docs/tutorials/rag-with-astradb.mdx
+++ b/docs/docs/tutorials/rag-with-astradb.mdx
@@ -20,9 +20,8 @@ In this guide, we will use Astra DB as a vector store to store and retrieve the
 TLDR;
 
 - [Create a free Astra DB account](https://astra.datastax.com/signup?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=create-a-free-astra-db-account)
-- Duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
 - Create a new database, get a **Token** and the **API Endpoint**
-- Click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components
+- Start Langflow and click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components
 - Import the project into Langflow by dropping it on the Workspace or My Collection page
 - Update the **Token** and **API Endpoint** in the **Astra DB** components
 - Update the OpenAI API key in the **OpenAI** components